Sampling Nomads: A New Technique for Remote, Hard-to-Reach, and Mobile Populations

Kristen Himelein 1 , Stephanie Eckman 2 , and Siobhan Murray 3
  • 1 World Bank – Development Economics Research Group, 1818 H St. NW Washington District of Columbia 20433, U.S.A.
  • 2 Institute for Employment Research, Nuremberg, Germany.
  • 3 World Bank – Development Economics Research Group, Washington, District of Columbia, U.S.A.


Livestock are an important component of rural livelihoods in developing countries, but data about this source of income and wealth are difficult to collect due to the nomadic and seminomadic nature of many pastoralist populations. Most household surveys exclude those without permanent dwellings, leading to undercoverage. In this study, we explore the use of a random geographic cluster sample (RGCS) as an alternative to the household-based sample. In this design, points are randomly selected and all eligible respondents found inside circles drawn around the selected points are interviewed. This approach should eliminate undercoverage of mobile populations. We present results of an RGCS survey with a total sample size of 784 households to measure livestock ownership in the Afar region of Ethiopia in 2012. We explore the RGCS data quality relative to a recent household survey, and discuss the implementation challenges.

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